Intelligent space surveillance (T6)

Objective: Within this activity, new methods will be explored for identifying orbital objects of interest from different types of images or datasets acquired from various types of sensors, with a focus on detection under challenging conditions and low signal-to-noise ratio (SNR)

Research challenges / Novelty / Innovation
• Analysis and annotation of existing data
• Development of improved methodologies for data acquisition
• Development and training of AI models
• Subsystem integration
• System validation

Research results:
• Algorithms for automated image processing, including preprocessing, AI models for detection and identification, calibration acceleration algorithms, and algorithms for automatic target identification
• Methodology for optimal image stream acquisition to maximize surveillance results
• Algorithms for orbit determination and refinement of orbital parameters for objects with known orbits.
• A hardware/software system for real-time image acquisition and processing for space surveillance, with high sensitivity and high angular determination accuracy, with limited energy requirements.

Inovation:
• Original algorithms